Abordagem fuzzy para caracterização de incertezas estruturais e quantificação de riscos hidrológicos: estudo de caso do reservatório Orós no semiárido brasileiro

• Autor(a) principal: Raulino, João Batista de Sousa
• Data de Publicação: 2022
• Outros Autores: Malveira, Vanda Tereza Costa, Lima Neto, Iran Eduardo
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Institucional da Universidade Federal do Ceará (UFC)
• Texto Completo: http://www.repositorio.ufc.br/handle/riufc/69157
• topic: Números Fuzzy Triangulares (NFT); Incertezas; Risco; Semiárido; Vazão afluente

In Water Resources studies, the identification and characterization of uncertainties are important steps in the modeling of water systems, as they allow an understanding of the interactions between data, parameters and model structure. The risk of a system depends on the uncertainties present and how much they can make it vulnerable to external loads. Uncertainties are, therefore, the background where risks are generated. This research aimed to demonstrate the applicability of Triangular Fuzzy Numbers (NFTs) in the identification and characterization of hydrological uncertainties, as well as using them to quantify the risks of the associated water system. The methodology consisted of identifying and classifying the uncertainty in the streamflow due to two different sources that contrast regarding the drainage area of the Orós reservoir sub-basin, located in the State of Ceará, Brazil, characterizing it using NFTs and quantifying the fuzzy risk associated with using one or the other in the process of generating hydrological information. The results showed that the identified uncertainty is a structural uncertainty, and it was possible to characterize it through the characteristic elements of the NFT considering the semi-arid characteristics. The calculated risks demonstrate that considering the streamflow provided by the National Water Agency (ANA) instead of that from the Water Resources Management Company (COGERH) can affect the capacity of the system. In the numerical example to illustrate the impact of structural uncertainty, yield, a significant impact was observed on the real capacity of the water system. The risk of failure of the yield, determined from ANA’s data, was 24% higher than the 10% used to estimate the yield, when compared to the yield generated from COGERH’s data. The FTNs were able to characterize and quantify the risk of structural uncertainty in the studied system, demonstrating that the NFT is an applicable and useful tool in obtaining hydrological information for the Management of Water Resources.